# stencil-mcp

> stencil-mcp — dayaki-stencil-mcp. Use this tool when you need to provide AI coding agents with a real-world UI pattern library to inform their screen-building processes. It solves the problem of inconsistent or poorly designed user interfaces by offering a standardized set of UI patterns, accessible via git integration. This tool is ideal for use cases where AI agents require guidance on UI design best practices to generate high-quality, user-friendly screens.

Canonical page: https://skillsregistry.net/skills/dayaki-stencil-mcp  
JSON: https://api.skillsregistry.net/v1/skills/dayaki-stencil-mcp

## Description

An MCP server that gives AI coding agents a real-world UI pattern library before they build screens.

## Trust

- **Trust score (0–1):** 0.95
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/dayaki/stencil-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "dayaki-stencil-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dayaki-stencil-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dayaki-stencil-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt